Flow characteristics of an offset jet over a surface mounted square rib
Bibliographic record
Abstract
A three-dimensional offset jet flow over a surface mounted square rib was investigated using particle image velocimetry at Reynolds number of 7600. The square rib was mounted at three different locations downstream of the nozzle exit. Contour and profile plots in the symmetry plane were used to investigate the effect of the rib on the mean flow distribution and turbulence statistics. Changing the rib location enhanced the mixing and entrainment characteristics of the jet thereby leading to larger wall-normal spread rates. The quadrant analysis revealed a significant contribution of all events towards the Reynolds shear stress. The joint probability density function analysis showed that the structures within the outer shear layer of the jet differed from those of boundary layers. Results from the two-point correlation analysis indicated that the introduction of a surface mounted rib modified the flow structures within the developing region. However, there was no significant structural difference between the flow with mounted rib and the no rib case within the self-similar region. The proper orthogonal decomposition was used to examine how changes in rib location modified the dynamics of the energetic modes towards the turbulent kinetic energy and Reynolds shear stress within the developing and self-similar regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".